To meet the demand for wireless data traffic having increased since deployment of 4G (4th-Generation) communication systems, efforts have been made to develop an improved 5G (5th-Generation) or pre-5G communication system. Therefore, the 5G or pre-5G communication system is also called a ‘Beyond 4G Network’ or a ‘Post LTE System’.
The 5G communication system is considered to be implemented in higher frequency (mmWave) bands, e.g., 60 GHz bands, so as to accomplish higher data rates. To decrease propagation loss of the radio waves and increase the transmission distance, the beamforming, massive multiple-input multiple-output (MIMO), Full Dimensional MIMO (FD-MIMO), array antenna, an analog beam forming, large scale antenna techniques are discussed in 5G communication systems.
In addition, in 5G communication systems, development for system network improvement is under way based on advanced small cells, cloud Radio Access Networks (RANs), ultra-dense networks, device-to-device (D2D) communication, wireless backhaul, moving network, cooperative communication, Coordinated Multi-Points (CoMP), reception-end interference cancellation and the like.
In the 5G system, Hybrid FSK and QAM Modulation (FQAM) and sliding window superposition coding (SWSC) as an advanced coding modulation (ACM), and filter bank multi carrier (FBMC), non-orthogonal multiple access (NOMA), and sparse code multiple access (SCMA) as an advanced access technology have been developed.
Wireless Local Area Networks (WLANs) have been used to cover, at low cost, a “shadow area” where a wireless communication service is limited. That is, the WLAN is structured to expand a service area using an Access Point (AP).
In the WLAN, to use a communication service, a wireless device needs to select one AP and to connect to the selected AP. For example, in the WLAN, a wireless device provides a scheme for AP selection and AP connection based on Basic Service Set (BSS) load.
A beacon broadcast by the AP includes an element, a BSS load. The BSS refers to a set of one AP and various wireless devices connected to the AP. The BSS load refers to the amount of traffic managed by the AP and is divided into station count, channel utilization, and available admission capacity information. The station count means the number of wireless devices connected to the corresponding AP. The channel utilization means how many busy time slots exist with respect to the maximum number of time slots, 255. The available admission capacity means a time capacity that be provided by the AP under complete control.
The BSS load is sole load information that is provided by the AP in a neighboring wireless device. The wireless device supports a selection algorithm based on the BSS load information. The selection algorithm selects one of neighboring APs and connects to the selected AP. If the BSS load information is complete in real time, accurate feedbacks to wireless traffic be provided to neighboring wireless devices. Also, the wireless device is connected to a particular AP to predict wireless service quality provided by the AP before directly experiencing the traffic.
In the WLAN, various schemes, in addition to the selection algorithm based on the BSS load information, are provided to optimize the wireless communication quality of wireless devices existing in a particular space. An example of a representative scheme is efficiently distributing a wireless capacity.
With the wide spread of wireless devices such as smart phones, pads, and so forth, the number of Wireless Fidelity (WI-FI) wireless routers (APs) have gradually increased per unit area.
When a clear AP selection criterion is provided to a wireless device, the wireless device is autonomously connected to an AP capable of providing the best quality. Various algorithms, such as the selection algorithm based on the BSS load information, a selection algorithm based on Received Signal Strength (RSS), and the like, have been proposed.
A solution has been proposed in which when an AP is initially installed, a position of the AP is optimized or a signal magnitude (or strength) of the AP is limited to increase spatial reusability. In addition, a heterogeneous network selection algorithm exists for devices having various wireless communication functions, such as smart phones or the like, without limiting the range of wireless networks simply to WLANs.
Wireless media managing and monitoring techniques for efficiently using a wireless capacity have no problem theoretically. Also, in various experiments with simulation, the good performance of those techniques has been demonstrated. However, when the motive for sensing a wireless condition is a connection to a new AP, various problems occur.
First, prior to the connection to the new AP, a wireless device and an AP cannot communicate with each other. Except for transmission and reception of a probe request or response or a beacon to prepare for the connection, any data or control frame cannot be exchanged. Thus, there is no way to secure a value such as a packet error rate prior to the connection. It is desirable to search for a new item having a clear correlation with a wireless quality without depending on data traffic, rather than predicting a wireless quality by directly monitoring wireless traffic. In this regard, the BSS load information has a big advantage of being acquired from a beacon transmitted compulsorily by APs. However, there are not enough wireless routers of high performance, being capable of transmitting the corresponding information through the beacon.
Likewise, installation location optimization and signal strength adjustment for APs are not practical solutions, either. Unlike a cell network installed by a common carrier, an entity which installs a wireless AP varies from large enterprises to minority homes, so even when a particular entity optimizes an installation location, it is not certain that another entity will install a new AP according to the installation location. Moreover, it is not certain that an AP exists in a fixed location at all times because a wireless device switches to an infrastructure node, like a WLAN hotspot service of a smart phone.
For signal strength adjustment, to have a function of adjusting a signal strength adaptively to a surrounding situation, implementation of an AP is complex, increasing a cost. As a result, signal strength adjustment does not appeal to either distributors or consumers. Consequently, for an optimized wireless quality of a wireless device, the wireless device needs to suitably predict a wireless quality condition of neighboring APs, without expecting a function or system change of a neighboring AP, thereby guiding connection to an AP being highly likely to secure the best wireless quality.
The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.